Dyadic data analysis

Knight, A. P., & Humphrey, S. E. (2019). Dyadic data analysis. In S. E. Humphrey and J. M. LeBreton (Eds.), The Handbook for Multilevel Theory, Measurement, and Analysis, pp. 423-447. Washington, DC: American Psychological Association.

Accompanying R functions for the social relations model: http://apknight.org/pdSRM.R

Abstract. Many foundational theories in the social sciences rely upon assumptions about dyadic interpersonal perceptions, behaviors, and relationships. This chapter provides a broad introduction to foundational concepts and techniques in analyzing dyadic data. The authors describe in detail one specific approach to dyadic data analysis—the social relations model—and provide software functions for conducting the analysis using multilevel modeling in R. The value of dyadic data analysis is illustrated through a discussion of prior publications that have used this approach. The authors also provide a step-by-step empirical example of how to use the social relations model with multilevel modeling in R, focused on dyadic trust in workgroups. The chapter concludes with a discussion of alternative approaches, beyond the social relations model, for analyzing dyadic data.

Who defers to whom and why?

Joshi, A., & Knight, A. P. (2015). Who defers to whom and why? Implications of demographic differences and dyadic deference for team effectiveness. Academy of Management Journal, 58, 59-84.

Abstract. We develop and test predictions about how demographic differences influence dyadic deference in multidisciplinary research teams, and how differential patterns of dyadic deference emerge to shape team-level effectiveness. We present a dual pathway model that recognizes that two distinct mechanisms—task contributions and social affinity— account for how team members’ demographic attributes contribute to deference. Furthermore, we propose that the extent to which these different mechanisms are prevalent in a team has implications for the team’s research productivity, with deference based on social affinity detracting from it and deference based on task contributions enhancing it. Using longitudinal data from a sample of 55 multidisciplinary research teams comprising 619 scientists, we found general support for our conceptual model. Our findings underscore the importance of accounting for multiple interpersonal mechanisms to understand the complex, multilevel nature of deference in teams.